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2125: The Two Minds Future

2125: The Two Minds Future

As AI becomes increasingly intelligent and capable of competing with todays human tasks, I sometimes fast forward to imagine where this trajectory can lead to. I often see these CEOs and Gen Z entrepreneurs (especially outside the european countries as europe is renowned for work-life balance) claiming to put in 120-140 hours of work every week or at least advocating it for their employees (I’m not certain if it is possible to work 140 hrs a week and stay mentally healthy). In an academic environment, a typical work in my area of research such as for example creating a working digital twin for an agricultural test field can take well over two years with collaborations and other administrative tasks, because our work is often tied to our human limitations and may be here AI definitely acts as assistant to achieve this goals much faster. Even with AI, building something like a digital twin of an agri field might take more than two years – not because it’s technically impossible to do it within two weeks, but because usually in academics, less employees are hired for a given task and these employees also have a life outside work and lot of other things to take care of that cannot be anytime soon replaced or aided by AI (kids, hobbies, normal life’s ups and downs).

Now lets imagine that all 8 billion people are motivated to work those crazy 140 hours - everyone coding, collecting data, building AI systems, driving trains, buses etc. All this human effort, whether it’s physical work generating training data for a physical robot or direct AI or code development, would get fast-forwarded at an incredible pace. The end result? We’d probably end up with superintelligent AI, automated driving systems and armies of robots way sooner than expected. With this super intelligent AI, nobody’s will want to sit in front of a computer to code nor drive a vehicle any more. Even to access this super intelligence we need not sit in front of computer or stare at smartphones.Instead, we’ll probably have something way more direct - a digital twin, or better yet, a second mind, an AI mind that becomes part of us.

Todays Social Media already has both positive and negative impact on people’s minds, consuming the collective humanity’s time in significant proportions. Now these AI minds would be our smart phone in 100 years where brain can experience two minds. Its like how devices connect to Wi-Fi, except it’s our brains connecting directly to this AI mind. There are already some progress going on in brain interfaces and artificial general intelligence. All this progress will naturally merge into a second mind capable of communicating with our brain. These hypothetical AI minds could also change or evolve our biological minds to deal not only with body and other humans mind but also a second AI mind with super intelligence of entire humanity.

And with this mind setup, I will be able to switch between my biological mind and AI mind. When I talk to someone, I’ll never know if they’re using their AI mind to respond while their real mind is somewhere else. We could even get different versions of AI minds - maybe shopping for ones that come at different prices! Some of us might have our mind migrated to a robot while our body runs on the AI mind.

The interesting thing is, this AI mind would have access to all knowledge through LLMs and whatever else we develop. Our biological brain would be constantly learning from the AI mind. No more traditional schools or teachers needed - we’re just constantly learning from our own AI mind. The AI mind would also be learning from how our biological mind development and how it thinks. They’d work in perfect sync. Once they’re in harmony like that, you could even move between your biological body and a physical digital twin.

So we would have AI doctors who could fix any “mind bugs” - like if your AI mind goes offline or you can’t connect to it properly. The AI mind would always be monitoring your body’s vitals, so detailed it could spot cancer when it’s just 100 cells. It’s kind of like those yogis or enlightened people who say they can sense each organ working through chakra activation - except this would be the technological version. These are the some of the possibilities we’d have!

There was this Johnny Depp’s movie I watched back in 2014 while doing my master’s at Alabama - Transcendence, it was a flop movie though. Like in that movie, maybe everyone will get a mind that never dies in 2125. I think in 100 years, we won’t have the same problems they had in that movie from 2014. I mean, I didn’t get inspired by this movie for this blog, but as I’m writing this, it just popped into my mind? It was actually one of the movies I really enjoyed back then.

So let’s say we have this technology working perfectly, not sinister like in the movie. Everything’s good, I’m sitting there with this AI mind (not just me, erery one, this mind is 2125’s chatGPT), robots making my coffee and everything (if I survive to see that day, I wont). But then what? What’s the purpose? Maybe I’d end up enjoying just doing physical work, farming, or watering plants. You know, enjoying nature, sunshine, rain - we’d be going in one full circle! That’s exactly what people used to do before industrial revolution. Maybe we created all this complexity, and now AI takes that complexity away. But there’s this enormous risk - what if it doesn’t work as intended? I mean, it’s one thing if someone hacks your laptop, but what if they hack your mind? That’s scary.

But even if everything goes perfectly utopian, what’s the human relevance then? Sure, we’ll have spiritual values, physical work, enjoying nature - all this existed before modern technology anyway. Maybe ultimate technology will remove human suffering like diseases and stuff. But for healthy people? They might just go back full circle. Though for people with challenges, like those without legs or vision, this technology would be amazing! I’m just thinking from a normal, healthy person’s perspective - maybe we’ll end up enjoying the simple things again. Who knows, maybe someday coding on a laptop will feel as outdated as enjoying a day at the beach.

Here we are in 2025 with AI that can tap into all human knowledge through a chat window affecting trillion worth economy. By 2125, we might each have our own digital twin, just endless conversations with our AI digital twin. What kind of economic system’s will handle that? What currency will we even use? Sure, we can see where the science is headed, but if it moves too fast, we could end up somewhere pretty dangerous. As we push forward, we’ve got to think about what all this means for everyone. Maybe it’s all about finding that sweet spot - not too much, not too little.

If we’ve got nuclear plants powering all these digital twins, and robots doing all the physical work, what are we 8 billion humans even here for? We’re using all our energy right now to build this perfect AI world, but once it’s done… then what? Maybe we’ll end up right back where we started, but with this crazy advanced tech running in the background. It’s interesting to think about, right? So I will end here this blog.

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My Academic Journey until 2020

Welcome to My Journey in Academia

Programming has been a significant part of my academic life for the past 15 years. From simulating the Sun to modeling plants, I’ve explored various aspects of the world around us through numerical methods. Looking back, it’s been a journey filled with challenges, discoveries, and growth.

In this blog, I want to share my programming journey and academic experiences—not as a polished narrative, but as a candid recollection of what comes to mind. Right now, programming skills are how I earn my bread and butter. Reflecting on where I started, what I learned, and the moments where I stumbled, I hope to capture the essence of my path so far.

This is my first blog post on my website, and it’s more about revisiting the milestones that brought me here. I’ll write, reflect, and edit iteratively as I go—just like coding, where nothing is perfect on the first run.

2006-2010: The Beginning

My programming journey began with the very first program I wrote in 2006. After that over the past 15 years, I’ve spent most of my time programming and simulating different things that make up a part of this world using numerical methods. But after all this time and work, if I try to recall my earliest days in coding, only bits and pieces come back to me. We can’t remember everything, can we? What I do remember of my academic and programming journey, I wanted to share here in my very first blog on my website.

During my bachelor’s in Electronics and Communication engineering (around 2007 to 2010) at BMSIT, Bengaluru, I remember writing sorting algorithms in C++ and working on microcontroller programming in assembly language. I was working with MATLAB, where I only remember implementing high-pass, low-pass, and band-pass filters. These stand out as strong memories, even though there were countless other programming exercises across various subjects.

So, don’t think I was very interested in programming. During this time, I actually thought programming was technically inferior as compared to designing physical circuits, antennas, or other electronic devices. But eventually, it became a part of my career. Till now, I have survived with it. And so, I will share more of my stories, like my master’s and PhD, down the line. But I just wanted to clarify that I was not at all passionate about programming in the beginning, and I don’t even claim that I’ve achieved something big, like inventing a new programming language. What I am trying to say is, right now, I can comfortably earn my bread and butter with programming. That’s why I thought of writing this blog.

My Masters Saga in USA (2010-2014)

In 2010, I finished my bachelor’s degree. What I wanted was to pursue higher studies in an international environment. And of course, the obvious choice—even now—is the United States. It attracts a lot of people, and during my time, I also went to the United States to do my master’s degree. In 2010, I joined the University of Alabama in Huntsville to study electrical engineering.

Back then, the fees were high for a lower middle-class Indian family, just like they are today. To make it work, my parents had to part with almost 50% of their life savings. So, once I got to the U.S., I had to figure out ways to save or make money while studying. One obvious way was to get a graduate research assistantship or a teaching assistantship.

However, coming from India with developing English language skills, it was challenging. My GRE verbal score wasn’t that impressive (330/800), though I scored very high in quantitative (780/800)—90th percentile, which means I did better than 90% of the test-takers. But even with that, my emerging English skills made it harder to secure a teaching assistantship.

In those days, we didn’t have ChatGPT or Deepseek to help us improve our English, like the way it’s helping me write this blog now in 2025. So, my options were limited. I didn’t have the opportunity to attend elite research universities like Stanford or MIT, where students pursuing their research could study on scholarships and explore topics on their own, and these places had large endowments to support such independent activity. But outside these places, there were few options for me. I had to fit into a project that had funding, whether it interested me or not, as it was a great deal if I could save money by helping a professor (which means less burden on my parents, who believed that a degree would lead to a stable future) finish their project and I could also learn a few things. But for me, learning science has always been the same. After working in many areas, I barely notice any boundary between disciplines. Whether I’m dealing with Darcy’s law or Ohm’s law, my satisfaction as a numerical scientist doesn’t change.

So coming back to my Masters degree, opportunities were limited, and only a few professors had funding. I ended up choosing Late Prof. Nagendra Singh as my Master’s thesis adviser, who was working in computational plasma physics employing methods like particle in cell and Magnetohydrodynamics (a kind of CFD), even though it was very new to me. Prior to this, I had no idea what plasma was, except in my high school I heard it as 4th state of matter and that it was present in the Sun.

I took on a thesis under him because it offered a graduate research assistantship that reduced my fees and expenses. This was the first time I was pushed into the world of computing and modeling because my job required me to learn Linux, supercomputing, and other tools. And so, out of necessity—to save money and complete my master’s degree—I was introduced to supercomputing and PHYSICS.

This was the first time I encountered Linux, which, surprisingly, wasn’t part of my undergraduate curriculum in India. It seems Linux is only taught in computer science programs, but I feel it should be introduced across all branches of engineering. Back then, around 2010-2011, Stack Overflow and online forums were my online gurus. Google was like the GPT of that era for me. Those were the days I learned about command-line interfaces, running jobs on supercomputing clusters, and the concept of software licenses.

Until then, I had taken software like MATLAB for granted. In my undergraduate days, I used it on university computers without considering who paid for it. But during my master’s, when I needed it for home assignments, I discovered that I needed to pay for a student edition and a company called Mathworks makes this software. I grew up with floppy drives and now I’m living with Thunderbolt 5. So we can’t compare with today.

I also had to learn about parallel computing, learning about MPI and OpenMPI for messy Fortran codes. Python wasn’t as mainstream as it is today, so I worked primarily with MATLAB and Fortran.

So, let me also share what exactly was my work during my master’s degree. There was this 2,000-line Fortran code my professor gave me, and honestly, it was the first time I realized that a code could even exceed 2,000 lines! Back in my bachelor’s, whether it was a band-pass filter or a Fourier transform, most of our lab exercises were 50 lines of code at most. This was on a completely different level.

The task was to modify this massive code because it didn’t compute the magnetic field of a Helmholtz coil. My professor asked me to write a function for that, solve it numerically using the Biot-Savart law, integrate it, and then parallelize it using MPI. The goal was to model how plasma flows in an experimental device and compare the results with actual experiments conducted at the Australian National University.

First, I wrote a code to solve the Biot-Savart law. It wasn’t overly complex, but handling it in 3D added its own challenges. Then, I integrated this new functionality into the existing Fortran code, ensuring that the variables and logic aligned perfectly. It was like adding a new feature to a large, unfamiliar system. Somehow, I managed to finish this work in six months. Looking back, I wonder if it was the energy of youth or sheer necessity that pushed me through. It wasn’t easy, but it resulted in two publications.

If you ask me now whether this work made a significant impact, I’d say probably not. I feel that even if I had taken a non-thesis option or chosen a different field, it wouldn’t have mattered much in the long run. But at that time, getting published felt like winning a Nobel Prize. Seeing my name on a paper gave me immense pride. Those publications, which you’ll still find on my CV, form the basis of my contributions to the physics of plasma.

While working on this project, I developed a deep love for physics. It felt almost spiritual to me, and I began regretting my decision to pursue engineering instead of physics. This newfound passion drove me to apply for a PhD in physics. However, switching to a good university wasn’t straightforward. Navigating the application process in a foreign country was unclear to me, and I didn’t have strong recommendations.

In the same town, there was another university—a historically black university with many Indian faculty members. To satisfy my love for physics, I joined their PhD program. But the work there felt far from what I imagined physics would be. It mostly involved lab experiments, like working with biophysics and optics, which didn’t eventually align with my interests. I was handling polymer molecules, thin membranes, and chemicals like polybutadiene (I don’t remember exactly), often without proper safety measures. All I remember is there were no gas masks and the moment I used this chemical there were pins and needles in my skin as I inhaled it, and I felt more like a lab assistant handling chemicals rather than a physicist.

I had this romanticized idea that studying physics would take me back to the times of Newton or Gauss. I know I was mistaken now but not back then. My physics experience, at least in the PhD program I was in, felt mundane and uninspiring. After spending one and a half years there, I decided to move on. I converted my PhD into a master’s degree and returned to India. I came back with no solid plan, but the thought of pursuing a PhD still remained with me.

How I landed in Germany in 2015

In 2014, after leaving my PhD program, I returned to India and experienced a period of career transition. That period was a challenge. I spent time earning Coursera and other certificates, enhancing my LinkedIn profile, and trying to build visibility through platforms like MATLAB File Exchange as well as applying to PhD positions worldwide including IISc Bengaluru. I tried several times to get into IISc PhD programs after having 3 publications and two masters degrees from the USA, but wasn’t successful. The main reason I was interested in IISc is because of its location in Bengaluru which is my home town.

I eventually received two PhD opportunities in 2015, one in South Korea on windmill simulation and the other at the University of Paderborn in Germany in theoretical physics. I was fascinated by the idea of studying in Europe. Many of the great physicists I admired were from European institutions, and Germany especially stood out to me.

I should also explain why I liked Germany - I think it’s a great country to study and also very practical. If I look back at my experience with degrees from the US or other countries, they all required things like letters of recommendation, medical tests, and other formalities. I’m originally from India, and getting a US visa itself was a process. I received a pink slip (221g) during the process, and it wasn’t easy at all. On top of that, the fees for studying in the US were extremely high.

When I went to Belgium for my PhD, they required a medical test before I could even begin. Although I did complete my PhD in Belgium, the visa process wasn’t as straightforward as it was with Germany. I also have experience getting visas from Gulf countries, and they too require medical tests just like Belgium. Though I didn’t have any health concerns, I appreciate that Germany has a more streamlined process for international students.

They didn’t ask me for letters of recommendation or medical tests for the visa. They liked my profile based on my interview and gave me admission to their PhD program in Theoretical Physics at Paderborn, to which I’m still grateful. This was in the year 2015. It was in quantum physics, which fascinated me, but the level of background knowledge required was far beyond what I had. I didn’t have a strong foundation in theoretical physics, and after one year, I had to leave the program.

I did consider doing a PhD in India and even applied to some programs, including IISc, but I wasn’t successful. I’ll save that experience for another blog, so don’t assume I ruled out India as an option. However, at that time, I found the application process and overall system of European universities to be much more straightforward and practical. Interestingly, IISc itself was historically modeled after Western universities (British, American and German influence), so in many ways, choosing a European institution wasn’t a drastic shift — it was just a path that worked out better for me.

So coming back to my journey, leaving the PhD program at Paderborn was yet another learning experience. While in Germany, I picked up a few things—including Bitte and Danke—but I also had to accept my limitations in theoretical physics. Still, I was determined to complete a PhD and kept looking for opportunities.

That’s when I came across an opening at the University of Louvain in Belgium for a project on modeling the electrical signatures of plant roots. The topic intrigued me because it involved modeling, which I enjoyed, and plants, which had always fascinated me. At first, I thought, “What does the electrical signature of plants even mean?” But the idea was compelling enough for me to apply.

To my surprise, I received an offer in 2016—but not without challenges. One of the key requirements was a recommendation letter, which took some effort to secure.

My Experience with Recommendation Letters

At that time, I reached out to professors from the two universities where I had completed my master’s degrees in the US. Getting recommendation letters proved challenging. In the second university—where I’d briefly joined a PhD program before leaving—I sensed my departure hadn’t gone over well, so I felt uneasy asking for a letter. Still, I tried, but got no response. Sometimes, people focus on their own commitments and may not prioritize helping former students.

At the first master’s university, where I had a publication record, my main advisor for the plasma physics thesis had unfortunately passed away—he was already in his 70s when I worked with him. I hadn’t really connected with other professors there, so I had no one else to ask.

All of this made me reflect on the role of recommendation letters in academia. It seems the system sometimes creates unnecessary barriers—like they’re just filtering applications rather than really getting to know the candidate. An experienced professor or committee could rely on interviews and a candidate’s portfolio of work as well.

That said, there are definitely supportive professors who write excellent letters when needed. For instance, professors at the University of Paderborn in Germany were remarkably helpful. Even though I didn’t initially ask them for a recommendation—having left that PhD program as well—they still vouched for me for the Belgian PhD position. Without their support, I might not have completed a PhD at all. Those letters helped me secure my fellowship in Belgium, and my PhD adviser there even mentioned how positive my Paderborn supervisor’s recommendation had been!

My PhD (2016 to 2020) in Belgium

So, I got my Belgian visa and began my PhD at the University of Louvain. If you ask me what stands out from those years of research, it’s this: I learned how to create finite element meshes for very complicated geometry. Before my PhD, I was proficient in the finite difference method, but finite element methods were new territory for me.

In my earlier experiences—whether during my master’s or at the University of Paderborn in theoretical physics—coding always involved starting from scratch. I had to write everything myself. But during my PhD, I learned how to utilize ready-made software models developed from years of multiple PhD projects like EIDORS (tomography in MATLAB) or R-SWMS (plant modelling tool in Fortran). Whether it was for electrical resistivity tomography (EIDORS) or simulating plant roots (R-SWMS), the challenge was to use these tools in a synchronized way to solve my specific problem.

The specific problem I worked on during my PhD wasn’t something I defined myself. My professors had proposed the problem, secured funding for it, and I accepted the offer to work on it. The project was focused on quantifying the electrical signature of plant roots.

In a way, this is how the academic system works at least in Europe—it’s very structured. A project exists, funding is secured, and researchers are brought in to help solve the problem and complete the project. That’s how most PhDs work in Europe. Unlike in places like IITs or IISc in India or some elite rich universities like Yale or Harvard, where students often spend the first couple of years figuring out what they want to do, the PhD structure in Europe is more defined from the start.

The PhD problem was well-defined, which meant I could focus my energy on solving it without wandering aimlessly. Having such a structured PhD also gave me time to pursue other interests. For example, during my PhD, I finally learned to play the violin—something I had wanted to do for years but never had the time to even buy one. I wouldn’t call myself an expert now either, but I learned for about a year. At least in this lifetime, I had the chance to play a violin, and that was possible because my PhD project saved me time by being so focused.

In my opinion, professors are experienced enough to propose meaningful problems, and if they believe a problem is worth solving, it likely is. Our role, then, is to contribute to solving that problem, finish the project, and earn the degree. This doesn’t mean you lack independence in a well-defined project. These projects often operate within a larger framework, giving you the freedom to explore related ideas.

For instance, within my PhD’s broader framework of quantifying the electrical signature of roots, I worked on a smaller project to show that electrical anisotropy could be used as a root phenotyping parameter. While this idea was presented at conferences, it never got published. But that didn’t matter much to me at the time because it was an opportunity to explore something new within the boundaries of the larger project.

It’s a misconception that well-defined projects restrict creativity. In fact, I believe they’re better because they save time and allow for focused progress. When I look back now, at 35 as I am writing this blog, I truly understand the value of time. Anything that helps save time should be taken seriously.

Now coming back to the PhD work, If I had to pick my most significant contribution during my PhD, it would be developing finite element meshes in 3D for complex plant root systems. This was no small feat and was appreciated by my peers. Apart from that, my PhD work led to two first-author publications, with 80% of the paper writing being my own contribution, and the rest polished by my thesis supervisor.

This felt different from my master’s degree, where I also had three publications (two as the first author and one as the second). However, during my master’s, my writing was significantly revised by my thesis supervisor—more than 50% of it. Back then, I might have been generating results and figures, but I wasn’t structuring the papers myself. It felt like I was providing inputs, and they assembled the work into a coherent paper.

This experience gave me a broader perspective on publications in academia. While some places still value publication numbers above all else, I believe it’s the quality and originality of the contribution that matter more. But that’s a discussion for another blog.

Returning to my PhD, I worked extensively on simulating plant root water uptake. One of my tasks involved adapting a finite element software originally designed for medical imaging of heart and lung systems. This tool, developed in the UK, was repurposed for our experiments with maize root systems in a risotron setup. Creating finite element meshes for these complex geometries was challenging but rewarding.

Once I completed meshing a single root system, I scaled up my work. I automated tasks to simulate thousands of plants and their interactions. Automation was a significant skill I developed during my PhD. Before this, I would run one software, manually plot each result, and feel content. But during my PhD, I had to scale up these processes. By my fourth year, a single plant simulation that used to feel monumental had become just a DOT in a scatterplot of thousands of simulations.

This was also the time—around 2018—when I was introduced to Python. Although Python had been around for a while, it was new to me. I quickly grew fond of it and transitioned away from my old buddy MATLAB. From then on, Python became my primary tool for simulations and data processing.

In 2020, I defended my PhD thesis. This was during the COVID-19 pandemic, a time that brought its own set of challenges. When I defended my PhD in October 2020, the world had changed—it was the time of COVID. It was the first time I experienced lockdowns, restrictions, and the global impact of a pandemic. People were suffering everywhere, and the world felt like it had transformed overnight. Somehow, I managed to finish my PhD and return to India during this turbulent time. Looking back, it was surreal. But we made it through, and life moved on.

Conclusions

I think I’ll end this blog here. If there’s anything to take away from my journey, here’s what I’d advise:

  • Changing paths is okay but be mindful of time. I started in electronics, ventured into plasma physics, attempted theoretical physics, and finally finished my PhD in a mix of electrical engineering and plant modelling. Your first choice doesn’t have to be your final destination. I have a broad experience now to have confidence to work in any new discipline with ease.

  • University rankings aren’t everything. While I was once focused on university rankings, I’ve learned that what matters more is finding the right fit for your goals and circumstances. Some of my most valuable experiences came from unexpected places. For example, it was only after completing my PhD, during the COVID time when I was between jobs, that I learned about the existence of the stock market and the massive financial world it represents. I discovered that there are companies like BlackRock or Morgan Stanley handling trillions of dollars in transactions. It was eye-opening to realize how much of the world operates through these financial systems—something I had never thought about when I was employed.

  • Learn to think Algorithmically, regardless of your field. Even though I initially thought programming was technically inferior to hardware design, it became my bread and butter. Being adaptable with technology opens doors. Even now I see how difficult it is to find a job without this skill. Though we have LLMs now, programming skills remain essential.

  • Embrace structured opportunities. While the romantic notion of complete academic freedom is appealing, well-defined projects (like my Belgian PhD) can actually provide focus while still allowing room for creativity and side interests.

  • Build relationships respectfully. The professors at Paderborn provided recommendations even after I left their program, which proved important for my future. How you leave matters as much as how you start.

  • Time is precious. Looking back at 35, I now realize the immense value of time more than ever. Choosing structured programs and opportunities that respect your time while allowing you to grow both professionally and personally is crucial. Reflecting on my own journey—the challenges with recommendation letters or choosing paths that weren’t the right fit—I see how important it is to make informed decisions.

For example, just because I loved physics, I thought pursuing it academically would fulfill me. In hindsight, I could have simply watched MIT OpenCourseWare lectures or listened to great physicists like Michio Kaku for inspiration. Those are wonderful resources, but at the end of the day, we have to be practical. If a PhD degree was my goal, I should have chosen a structured program in Europe right after my first Master’s degree! Decisions can significantly impact our trajectory.

Now, some people might argue that research should stem purely from passion and interest, and that doing a PhD should be about a deep love for discovery. But in the era of ChatGPT, I feel research is essentially about critical thinking and solving problems. That’s all it is.

I don’t see much difference between the work I do in academia and the work people do in the industry. Both fields are about addressing pressing issues. We’re not necessarily discovering brand-new things—most foundational discoveries have already been made. We are, as they say, standing on the shoulders of giants.

Take, for instance, the discovery of the exponential number e. Jacob Bernoulli didn’t find it only out of pure curiosity—he was solving a financial problem related to compound interest. Similarly, Fourier series was developed by Joseph Fourier not just as a romantic pursuit of mathematics, but to address practical challenges during the Industrial Revolution, such as analyzing periodic heat flow in steam engines. In fact, the industrial revolution a few centuries back made the West dominant in science and technology.

Great scientific breakthroughs didn’t come from just loving science; they emerged from solving real-world problems. Science wasn’t—and isn’t—a romantic affair; it’s a practical endeavor that I learned through experience. Of course, I could be wrong—this is just my opinion. But I believe it’s worth reflecting on how much of what we do, whether in academia or industry, is rooted in solving practical challenges, just as it always has been.

Now, I understand that time is irreplaceable. Every moment should serve a purpose: it should either generate value for the future, enhance your profile, improve your mental or physical health, or bring genuine fulfillment. Time is finite, and how we spend it matters greatly—whether that’s working, learning, or simply resting.

It may feel late to realize this, but as they say, “better late than never.” From now on, I’ve committed to being intentional with my time, and I hope you will too. Respect your time—it’s the most valuable resource you have. Respect others’ time as well. Remember, these reflections come from my personal journey - yours might be different.

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